{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "google",
   "metadata": {},
   "source": [
    "##### Copyright 2023 Google LLC."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "apache",
   "metadata": {},
   "source": [
    "Licensed under the Apache License, Version 2.0 (the \"License\");\n",
    "you may not use this file except in compliance with the License.\n",
    "You may obtain a copy of the License at\n",
    "\n",
    "    http://www.apache.org/licenses/LICENSE-2.0\n",
    "\n",
    "Unless required by applicable law or agreed to in writing, software\n",
    "distributed under the License is distributed on an \"AS IS\" BASIS,\n",
    "WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
    "See the License for the specific language governing permissions and\n",
    "limitations under the License.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "basename",
   "metadata": {},
   "source": [
    "# vrp_items_to_deliver"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "link",
   "metadata": {},
   "source": [
    "<table align=\"left\">\n",
    "<td>\n",
    "<a href=\"https://colab.research.google.com/github/google/or-tools/blob/main/examples/notebook/constraint_solver/vrp_items_to_deliver.ipynb\"><img src=\"https://raw.githubusercontent.com/google/or-tools/main/tools/colab_32px.png\"/>Run in Google Colab</a>\n",
    "</td>\n",
    "<td>\n",
    "<a href=\"https://github.com/google/or-tools/blob/main/ortools/constraint_solver/samples/vrp_items_to_deliver.py\"><img src=\"https://raw.githubusercontent.com/google/or-tools/main/tools/github_32px.png\"/>View source on GitHub</a>\n",
    "</td>\n",
    "</table>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "doc",
   "metadata": {},
   "source": [
    "First, you must install [ortools](https://pypi.org/project/ortools/) package in this colab."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "install",
   "metadata": {},
   "outputs": [],
   "source": [
    "%pip install ortools"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "description",
   "metadata": {},
   "source": [
    "Vehicles Routing Problem (VRP) for delivering items from any suppliers.\n",
    "Description:\n",
    "Need to deliver some item X and Y at end nodes (at least 11 X and 13 Y).\n",
    "Several locations provide them and even few provide both.\n",
    "\n",
    "fleet:\n",
    "  * vehicles: 2\n",
    "  * x capacity: 15\n",
    "  * y capacity: 15\n",
    "  * start node: 0\n",
    "  * end node: 1\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "code",
   "metadata": {},
   "outputs": [],
   "source": [
    "from ortools.constraint_solver import routing_enums_pb2\n",
    "from ortools.constraint_solver import pywrapcp\n",
    "\n",
    "\n",
    "\n",
    "def create_data_model():\n",
    "    \"\"\"Stores the data for the problem.\"\"\"\n",
    "    data = {}\n",
    "    data['num_vehicles'] = 2\n",
    "    data['starts'] = [0] * data['num_vehicles']\n",
    "    data['ends'] = [1] * data['num_vehicles']\n",
    "    assert len(data['starts']) == data['num_vehicles']\n",
    "    assert len(data['ends']) == data['num_vehicles']\n",
    "\n",
    "    # Need 11 X and 13 Y\n",
    "    data['providers_x'] = [\n",
    "        0,  # start\n",
    "        -11,  # end\n",
    "        2,  # X supply 1\n",
    "        2,  # X supply 2\n",
    "        4,  # X supply 3\n",
    "        4,  # X supply 4\n",
    "        4,  # X supply 5\n",
    "        5,  # X supply 6\n",
    "        1,  # X/Y supply 1\n",
    "        2,  # X/Y supply 2\n",
    "        2,  # X/Y supply 3\n",
    "        0,  # Y supply 1\n",
    "        0,  # Y supply 2\n",
    "        0,  # Y supply 3\n",
    "        0,  # Y supply 4\n",
    "        0,  # Y supply 5\n",
    "        0,  # Y supply 6\n",
    "    ]\n",
    "    data['providers_y'] = [\n",
    "        0,  # start\n",
    "        -13,  # ends\n",
    "        0,  # X supply 1\n",
    "        0,  # X supply 2\n",
    "        0,  # X supply 3\n",
    "        0,  # X supply 4\n",
    "        0,  # X supply 5\n",
    "        0,  # X supply 6\n",
    "        3,  # X/Y supply 1\n",
    "        2,  # X/Y supply 2\n",
    "        1,  # X/Y supply 3\n",
    "        3,  # Y supply 1\n",
    "        3,  # Y supply 2\n",
    "        3,  # Y supply 3\n",
    "        3,  # Y supply 4\n",
    "        3,  # Y supply 5\n",
    "        5,  # Y supply 6\n",
    "    ]\n",
    "    data['vehicle_capacities_x'] = [15] * data['num_vehicles']\n",
    "    data['vehicle_capacities_y'] = [15] * data['num_vehicles']\n",
    "    assert len(data['vehicle_capacities_x']) == data['num_vehicles']\n",
    "    assert len(data['vehicle_capacities_y']) == data['num_vehicles']\n",
    "    data['distance_matrix'] = [\n",
    "        [\n",
    "            0, 548, 776, 696, 582, 274, 502, 194, 308, 194, 536, 502, 388, 354,\n",
    "            468, 776, 662\n",
    "        ],\n",
    "        [\n",
    "            548, 0, 684, 308, 194, 502, 730, 354, 696, 742, 1084, 594, 480, 674,\n",
    "            1016, 868, 1210\n",
    "        ],\n",
    "        [\n",
    "            776, 684, 0, 992, 878, 502, 274, 810, 468, 742, 400, 1278, 1164,\n",
    "            1130, 788, 1552, 754\n",
    "        ],\n",
    "        [\n",
    "            696, 308, 992, 0, 114, 650, 878, 502, 844, 890, 1232, 514, 628, 822,\n",
    "            1164, 560, 1358\n",
    "        ],\n",
    "        [\n",
    "            582, 194, 878, 114, 0, 536, 764, 388, 730, 776, 1118, 400, 514, 708,\n",
    "            1050, 674, 1244\n",
    "        ],\n",
    "        [\n",
    "            274, 502, 502, 650, 536, 0, 228, 308, 194, 240, 582, 776, 662, 628,\n",
    "            514, 1050, 708\n",
    "        ],\n",
    "        [\n",
    "            502, 730, 274, 878, 764, 228, 0, 536, 194, 468, 354, 1004, 890, 856,\n",
    "            514, 1278, 480\n",
    "        ],\n",
    "        [\n",
    "            194, 354, 810, 502, 388, 308, 536, 0, 342, 388, 730, 468, 354, 320,\n",
    "            662, 742, 856\n",
    "        ],\n",
    "        [\n",
    "            308, 696, 468, 844, 730, 194, 194, 342, 0, 274, 388, 810, 696, 662,\n",
    "            320, 1084, 514\n",
    "        ],\n",
    "        [\n",
    "            194, 742, 742, 890, 776, 240, 468, 388, 274, 0, 342, 536, 422, 388,\n",
    "            274, 810, 468\n",
    "        ],\n",
    "        [\n",
    "            536, 1084, 400, 1232, 1118, 582, 354, 730, 388, 342, 0, 878, 764,\n",
    "            730, 388, 1152, 354\n",
    "        ],\n",
    "        [\n",
    "            502, 594, 1278, 514, 400, 776, 1004, 468, 810, 536, 878, 0, 114,\n",
    "            308, 650, 274, 844\n",
    "        ],\n",
    "        [\n",
    "            388, 480, 1164, 628, 514, 662, 890, 354, 696, 422, 764, 114, 0, 194,\n",
    "            536, 388, 730\n",
    "        ],\n",
    "        [\n",
    "            354, 674, 1130, 822, 708, 628, 856, 320, 662, 388, 730, 308, 194, 0,\n",
    "            342, 422, 536\n",
    "        ],\n",
    "        [\n",
    "            468, 1016, 788, 1164, 1050, 514, 514, 662, 320, 274, 388, 650, 536,\n",
    "            342, 0, 764, 194\n",
    "        ],\n",
    "        [\n",
    "            776, 868, 1552, 560, 674, 1050, 1278, 742, 1084, 810, 1152, 274,\n",
    "            388, 422, 764, 0, 798\n",
    "        ],\n",
    "        [\n",
    "            662, 1210, 754, 1358, 1244, 708, 480, 856, 514, 468, 354, 844, 730,\n",
    "            536, 194, 798, 0\n",
    "        ],\n",
    "    ]\n",
    "    assert len(data['providers_x']) == len(data['distance_matrix'])\n",
    "    assert len(data['providers_y']) == len(data['distance_matrix'])\n",
    "    return data\n",
    "\n",
    "\n",
    "def print_solution(data, manager, routing, assignment):\n",
    "    \"\"\"Prints assignment on console.\"\"\"\n",
    "    print(f'Objective: {assignment.ObjectiveValue()}')\n",
    "    # Display dropped nodes.\n",
    "    dropped_nodes = 'Dropped nodes:'\n",
    "    for node in range(routing.Size()):\n",
    "        if routing.IsStart(node) or routing.IsEnd(node):\n",
    "            continue\n",
    "        if assignment.Value(routing.NextVar(node)) == node:\n",
    "            dropped_nodes += f' {manager.IndexToNode(node)}'\n",
    "    print(dropped_nodes)\n",
    "    # Display routes\n",
    "    total_distance = 0\n",
    "    total_load_x = 0\n",
    "    total_load_y = 0\n",
    "    for vehicle_id in range(manager.GetNumberOfVehicles()):\n",
    "        index = routing.Start(vehicle_id)\n",
    "        plan_output = f'Route for vehicle {vehicle_id}:\\n'\n",
    "        route_distance = 0\n",
    "        route_load_x = 0\n",
    "        route_load_y = 0\n",
    "        while not routing.IsEnd(index):\n",
    "            node_index = manager.IndexToNode(index)\n",
    "            route_load_x += data['providers_x'][node_index]\n",
    "            route_load_y += data['providers_y'][node_index]\n",
    "            plan_output += f' {node_index} Load(X:{route_load_x}, Y:{route_load_y}) -> '\n",
    "            previous_index = index\n",
    "            previous_node_index = node_index\n",
    "            index = assignment.Value(routing.NextVar(index))\n",
    "            node_index = manager.IndexToNode(index)\n",
    "            #route_distance += routing.GetArcCostForVehicle(previous_index, index, vehicle_id)\n",
    "            route_distance += data['distance_matrix'][previous_node_index][node_index]\n",
    "        node_index = manager.IndexToNode(index)\n",
    "        plan_output += f' {node_index} Load({route_load_x}, {route_load_y})\\n'\n",
    "        plan_output += f'Distance of the route: {route_distance}m\\n'\n",
    "        plan_output += f'Load of the route: X:{route_load_x}, Y:{route_load_y}\\n'\n",
    "        print(plan_output)\n",
    "        total_distance += route_distance\n",
    "        total_load_x += route_load_x\n",
    "        total_load_y += route_load_y\n",
    "    print(f'Total Distance of all routes: {total_distance}m')\n",
    "    print(f'Total load of all routes: X:{total_load_x}, Y:{total_load_y}')\n",
    "\n",
    "\n",
    "def main():\n",
    "    \"\"\"Entry point of the program.\"\"\"\n",
    "    # Instantiate the data problem.\n",
    "    data = create_data_model()\n",
    "\n",
    "    # Create the routing index manager.\n",
    "    manager = pywrapcp.RoutingIndexManager(len(data['distance_matrix']),\n",
    "                                           data['num_vehicles'], data['starts'],\n",
    "                                           data['ends'])\n",
    "\n",
    "    # Create Routing Model.\n",
    "    routing = pywrapcp.RoutingModel(manager)\n",
    "\n",
    "\n",
    "    # Create and register a transit callback.\n",
    "    def distance_callback(from_index, to_index):\n",
    "        \"\"\"Returns the distance between the two nodes.\"\"\"\n",
    "        # Convert from routing variable Index to distance matrix NodeIndex.\n",
    "        from_node = manager.IndexToNode(from_index)\n",
    "        to_node = manager.IndexToNode(to_index)\n",
    "        return data['distance_matrix'][from_node][to_node]\n",
    "\n",
    "    transit_callback_index = routing.RegisterTransitCallback(distance_callback)\n",
    "\n",
    "    # Define cost of each arc.\n",
    "    routing.SetArcCostEvaluatorOfAllVehicles(transit_callback_index)\n",
    "\n",
    "    # Add Distance constraint.\n",
    "    dimension_name = 'Distance'\n",
    "    routing.AddDimension(\n",
    "        transit_callback_index,\n",
    "        0,  # no slack\n",
    "        2000,  # vehicle maximum travel distance\n",
    "        True,  # start cumul to zero\n",
    "        dimension_name)\n",
    "    distance_dimension = routing.GetDimensionOrDie(dimension_name)\n",
    "    # Minimize the longest road\n",
    "    distance_dimension.SetGlobalSpanCostCoefficient(100)\n",
    "\n",
    "\n",
    "    # Add Capacity constraint.\n",
    "    def demand_callback_x(from_index):\n",
    "        \"\"\"Returns the demand of the node.\"\"\"\n",
    "        # Convert from routing variable Index to demands NodeIndex.\n",
    "        from_node = manager.IndexToNode(from_index)\n",
    "        return data['providers_x'][from_node]\n",
    "\n",
    "    demand_callback_x_index = routing.RegisterUnaryTransitCallback(\n",
    "        demand_callback_x)\n",
    "    routing.AddDimensionWithVehicleCapacity(\n",
    "        demand_callback_x_index,\n",
    "        0,  # null capacity slack\n",
    "        data['vehicle_capacities_x'],  # vehicle maximum capacities\n",
    "        True,  # start cumul to zero\n",
    "        'Load_x')\n",
    "\n",
    "    def demand_callback_y(from_index):\n",
    "        \"\"\"Returns the demand of the node.\"\"\"\n",
    "        # Convert from routing variable Index to demands NodeIndex.\n",
    "        from_node = manager.IndexToNode(from_index)\n",
    "        return data['providers_y'][from_node]\n",
    "\n",
    "    demand_callback_y_index = routing.RegisterUnaryTransitCallback(\n",
    "        demand_callback_y)\n",
    "    routing.AddDimensionWithVehicleCapacity(\n",
    "        demand_callback_y_index,\n",
    "        0,  # null capacity slack\n",
    "        data['vehicle_capacities_y'],  # vehicle maximum capacities\n",
    "        True,  # start cumul to zero\n",
    "        'Load_y')\n",
    "\n",
    "    # Add constraint at end\n",
    "    solver = routing.solver()\n",
    "    load_x_dim = routing.GetDimensionOrDie('Load_x')\n",
    "    load_y_dim = routing.GetDimensionOrDie('Load_y')\n",
    "    ends = []\n",
    "    for v in range(manager.GetNumberOfVehicles()):\n",
    "        ends.append(routing.End(v))\n",
    "\n",
    "    node_end = data['ends'][0]\n",
    "    solver.Add(\n",
    "        solver.Sum([load_x_dim.CumulVar(l)\n",
    "                    for l in ends]) >= -data['providers_x'][node_end])\n",
    "    solver.Add(\n",
    "        solver.Sum([load_y_dim.CumulVar(l)\n",
    "                    for l in ends]) >= -data['providers_y'][node_end])\n",
    "    #solver.Add(load_y_dim.CumulVar(end) >= -data['providers_y'][node_end])\n",
    "\n",
    "    # Allow to freely drop any nodes.\n",
    "    penalty = 0\n",
    "    for node in range(0, len(data['distance_matrix'])):\n",
    "        if node not in data['starts'] and node not in data['ends']:\n",
    "            routing.AddDisjunction([manager.NodeToIndex(node)], penalty)\n",
    "\n",
    "    # Setting first solution heuristic.\n",
    "    search_parameters = pywrapcp.DefaultRoutingSearchParameters()\n",
    "    search_parameters.first_solution_strategy = (\n",
    "        routing_enums_pb2.FirstSolutionStrategy.PATH_CHEAPEST_ARC)\n",
    "    search_parameters.local_search_metaheuristic = (\n",
    "        routing_enums_pb2.LocalSearchMetaheuristic.GUIDED_LOCAL_SEARCH)\n",
    "    # Sets a time limit; default is 100 milliseconds.\n",
    "    #search_parameters.log_search = True\n",
    "    search_parameters.time_limit.FromSeconds(1)\n",
    "\n",
    "    # Solve the problem.\n",
    "    solution = routing.SolveWithParameters(search_parameters)\n",
    "\n",
    "    # Print solution on console.\n",
    "    if solution:\n",
    "        print_solution(data, manager, routing, solution)\n",
    "    else:\n",
    "        print('no solution found !')\n",
    "\n",
    "\n",
    "main()\n",
    "\n"
   ]
  }
 ],
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 "nbformat_minor": 5
}
